But what if we want the latest Percona Server or MariaDB for this recipe? One solution would be to run the script with an argument, but we can ask dbdeployer to find the most recent version for a given flavor and use it in our recipe:

This works for all the recipes that don’t require a given flavor. When one is indicated (see dbdeployer cookbook list) you can override it using --flavor, but do that at your own risk. Running the ndb recipe using pxc flavor won’t produce anything usable.

Replication between sandboxes

When I proposed dbdeployer support for NDB, the immediate reaction was that this was good to test cluster-to-cluster replication. Although I did plenty of such topologies in one of my previous jobs, I had limited experience replicating between single or composite sandboxes. Thus, I started thinking about how to do it. In the old MySQL-Sandbox, I had an option --slaveof that allowed a single sandbox to replicate from an existing one. I did not implement the same thing in dbdeployer, because that solution looked limited, and only useful in a few scenarios.

I wanted something more dynamic, and initially I thought of creating a grandiose scheme, involving custom templates and user-defined fillers. While I may end up doing that some day, I quickly realized that it was overkill for this purpose, and that the sandboxes had already all the information needed to replicate from and to every other sandbox. I just had to expose the data in such a way that it can be used to plug one sandbox to the other.

Now every sandbox has a script named replicate_from, and a companion script called metadata. Using a combination of the two (in fact, replicate_from on the would-be replica calls metadata from the donor) we can quickly define the replication command needed for most situations.

Replication between single sandboxes

Before we tackle the most complex one, let’s demonstrate that the system works with a simple case.

There is a recipe named replication_between_single that creates a file named, aptly, ./recipes/replication-between-single.sh.

The script deploys two sandboxes of the chosen version, using different directory names (dbdeployer takes care of choosing a free port) and then starts replication between the two using $SANDBOX1/replicate_from $SANDBOX2. Then a quick test shows that the data created in a sandbox can be retrieved in the other.

Replication between group replication clusters

The method used to replicate between two group replications is similar to the one seen for single sandboxes. The script replicate_from on the group top directory delegates the replication task to its first node, which points to the second group.

The interesting thing about this recipe is that the sandboxes are created using the option --port-as-server-id. While it was used also in the replication between single sandboxes as an excess of caution, in this recipe, and in all the recipes involving compound sandboxes, it is a necessity, as the replication would fail if primary and replica servers have the same server_id.

All the work is done by the replicate_from script, which knows how to check whether the target is a single sandbox or a composite one, and where to find the primary server.

Using a similar method, we can run more recipes on the same tune.

Replication between different things

I won’t reproduce the output of all recipes here. I will just mention what every recipe needs to prepare to ensure a positive outcome.

Replication between NDB clusters. Nothing special here, except making sure to use a MySQL Cluster tarball. If you don’t dbdeployer will detect it and refuse the installation. For the rest, it’s like replication between groups.

Replication between master/slave. This is a bit trickier, because the replication data comes to a master, and if we want to propagate to its slaves we need to activate log-slave-update. The recipe shows how to do it.

Replication between group and master/slave. In addition to the trick mentioned in the previous recipe, we need to make sure that the master/slave deployment is using GTID.

Replication between master/slave and group. See the previous one.

Replication between group and single (and vice versa). We just need to make sure the single sandbox has GTID enabled.

Replication between different versions

This is a simple recipe that comes from a feature request. All you need to do is make sure that the version on the master is lower than the one on the slaves. The recipe script replication-multi-versions.sh, looks for tarballs of 5.6, 5.7, and 8.0, but you can start it using three versions that you’d like. For example:

./recipes/replication-multi-versions.sh 5.7.23 5.7.24 5.7.25

The first version will be used as the master.

Circular replication

I didn’t want to do this, as I consider ring replication to be weak and difficult to handle. I stated that much in the feature request and in the list of dbdeployer features. But then I saw that with the latest enhancements it was so easy, that I had to at least make a recipe for it. And then you have it. recipes/circular-replication.sh does what it promises, but the burden of maintenance is still on the user’s shoulders. I suggest looking at it, and then forgetting it.

Upgrade from MySQL 5.5 to 8.0 (through 5.6 and 5.7)

This is one of the most advanced recipes. To enjoy it, you need to have expanded tarballs from 5.5, 5.6, 5.7, and 8.0.

Provided that you do, running this script will do the following:

deploy MySQL 5.5

Create a table upgrade_log and insert some data.

deploy MySQL 5.6

run mysql_upgrade (through dbdeployer)

Add data to the log table

deploy MySQL 5.7

run mysql_upgrade again

add data to the log table

deploy MySQL 8.0

run mysql_upgrade for the last time

Show the data from the table

Here’s a full transcript of the operation. It’s interesting to see how the upgrade procedure has changed from older versions to current ones.

What else can we do?

The replication recipes seen so far use the same principles. The method used in these recipes doesn’t work for all-masters and fan-in replication, because mixing named channels and nameless ones is not allowed. Also, there are things that don’t respond to replication commands at all, like TiDB. But it should be easy to enhance the current scripts (or to add some more specialized ones) that will include also these exceptions. Given the recent wave of collaboration, I expect it will happen relatively soon.

Friday, March 29, 2019

When I designed dbdeployer, I wanted to eliminate most of the issues that the old MySQL-Sandbox had:

dependencies during installation

mistaken tarballs

clarity of syntax

features (un)awareness.

Dependencies during installation did go away right from the start, as the dbdeployer executable is ready to be used without additional components. The only dependency is to have a host that can run MySQL. There is little dbdeployer can do about detecting whether or not your system can run MySQL. It depends on which version and flavor of MySQL you are running. It should not be a big deal as I assume that anyone in need of dbdeployer has already the necessary knowledge about MySQL prerequisites. This is not always the case, but the issue goes beyond dbdeployer’s scope.

Mistaken tarballs are a common problem for users who have never seen a binaries tarball. Here dbdeployer can help, up to a point, to guide the user. It recognizes most cases where you are trying to use a source tarball or the wrong operating system tarball. It still does not recognize when you try to run a sandbox for a Linux 64bits out of a 32bit tarball, but to be honest I haven’t tried to solve this problem yet. There are still cases where users are a great risk of picking the wrong tarball (Percona Server download page is a minefield and the one for MariaDB is not picnic either) but I feel that I have given dbdeployer users a big help on this count.

Clarity of syntax is probably the biggest issue with the previous tool. It’s a consequence of the tool being developed over several years, slowly adapting to changing circumstances. I made dbdeployer clearer from the beginning, when I decided to avoid piling up many actions as the consequence of the same command. In dbdeployer, you need to unpack the tarball explicitly before running a deployment, and this gives dbdeployer users the visibility on the architecture that eluded many MySQL-Sandbox users. The architecture of dbdeployer is such that adding new features, commands, and options is easy and fits within an easily detectable paradigm. Thus, the operations are easier to spot and use.

Features awareness is still a problem. There is a lengthy description of everything dbdeployer can do, but, as often happens with even the best tools, users don’t read manuals.

The biggest obstacle about reading manuals is that dbdeployer executable is installed without any need to take the README file along. If you need it, you should go online and read it, and given that dbdeployer is built to be used mostly without internet connection, there are cases when you want to know how to do something, but you can’t get the manual right away.

There is the tool integrated help (dbdeployer [command] -h), which gives you a lot of information, but this tells you how to do something that you know already exists, not what you can do in general.

To help on this count, I added a collection of samples (the cookbook) that were initially released in a directory of the GitHub project, but then the sample scripts suffered of the same invisibility that plagues the README file. There is one more problem: when you tried using the generic cookbook scripts (now removed) you had to use the same environment as I did when defining them, or they would fail.

The current solution is to include cookbook files right within the tool, using templates (same as for regular sandbox scripts) with the double advantage that the scripts are available anywhere the dbdeployer executable is, and the scripts are adapted to the environment, since dbdeployer knows how to search for available binaries and can suggest the best parameters for the scripts.

Introducing dbdeployer cookbook

The command dbdeployer cookbook (with aliases recipes or samples) has three subcommands:

There! instead of the NOTFOUND we saw before, it now shows the version that we just downloaded. If we repeat the same procedure (remote list, remote get, unpack) for MySQL 8.0.15, we would see 8.0.15 as the recommended version.

Now we can create the single recipe. Or even better, since we want to try several ones, we can create all of them.

$ dbdeployer cookbook create all
recipes/replication-between-master-slave.sh created
recipes/single-reinstall.sh created
recipes/fan-in-deployment.sh created
recipes/group-multi-primary-deployment.sh created
recipes/repl-operations.sh created
recipes/tidb-deployment.sh created
recipes/remote.sh created
recipes/upgrade.sh created
recipes/ndb-deployment.sh created
recipes/cookbook_include.sh created
recipes/master-slave-deployment.sh created
recipes/prerequisites.sh created
recipes/replication-between-groups.sh created
recipes/replication-between-ndb.sh created
recipes/pxc-deployment.sh created
recipes/single-deployment.sh created
recipes/show-sandboxes.sh created
recipes/delete-sandboxes.sh created
recipes/all-masters-deployment.sh created
recipes/group-single-primary-deployment.sh created
recipes/repl-operations-restart.sh created

Tuesday, March 19, 2019

I remember wanting to create MySQL Cluster sandboxes several years ago. By then, however, MySQL-Sandbox technology was not flexible enough to allow an easy inclusion, and the cluster software itself was not as easy to install as it is today. Thus, I kept postponing the implementation, until I started working with dbdeployer.

I included the skeleton of support for MySQL Cluster since the beginning (by keeping a range of ports dedicated for this technology, but I didn’t do anything until June 2018, when I made public my intentions to add support for NDB in dbdeployer with issue #20 (Add support for MySQL Cluster)). The issue had just a bare idea, but I needed help from someone, as my expertise with NDB was limited, and outdated.

Help came in November, when Daniël van Eeden started giving me bits of information on how to put together a cluster sandbox. I still resisted forcing my hand at the implementation, because by then I had realised that my method of checking the database server version to know whether it supported a given feature was inadequate to support anything other than vanilla MySQL or fully complaint forks.

When I finally decided to start working on NDB, it took me only a few days to implement it, because I had all the pieces ready for this technology to become part of dbdeployer.

Following Däniel’s instructions, I had a prototype working, which I submitted to #dbdeployer channel on MySQL community slack. In that channel, I got help again from Däniel van Eeden, and then Frédéric Descamps summoned two more experts (Ted Wennmark and Bernd Ocklin), who gave me feedback, advice, and some quick lessons on how the cluster should work, which allowed me to publish a release (dbdeployer 1.23.0) this past week-end.

The implementation has some peculiarities for both users of dbdeployer and MySQL Cluster. For the ones used to dbdeployer, the biggest change is that we are deploying two entities, of which the main one is an NDB cluster, with its own directories and processes, while the MySQL servers are just the visible part of the cluster, but are, in fact, only cluster clients. Still, the cluster works smoothly in dbdeployer paradigm: the cluster is deployed (like Group replication or PXC) as a replication topology, and as such we can run the standard replication test and expect to get the same result that we would see when checking another multi-source deployment.

For people used to NDB, though, seeing NDB as “replication” feels odd, because the cluster is seeing as a distinct entity, and replication is when we transfer data between two clusters. If we were developing a dedicated tool for NDB clusters, this is probably what we would have done, but since we want dbdeployer integration, we must play by the general rules of the tool, where “single” is a stand-alone server instance, and we can’t have dbdeployer deploy single --topology=ndb, because single instance don’t have a topology, which is a property of a group of entities. Therefore, the price to pay for dbdeployer support accepting to see a MySQL cluster deployment as replication.

Now that we have covered all the philosophical angle, it’s time to show an example. Unlike PXC, which is requires Linux, MySQL Cluster can also run on MacOS, which makes my testing much easier.

The first step to run a cluster in dbdeployer is to download a tarball from dev.mysql.com/downloads/cluster, and then expand it in our usual directory ($HOME/opt/mysql):

It is possible that we will need more iterations to make the deployment more robust. When testing it, keep in mind that this deployment is only for testing, and it won’t probably have all the performance that you may find in a well deployed production cluster. Still, compared to other topologies, the replication tests performed faster than I expected.

Friday, March 08, 2019

This was not on the radar. I have never been proficient in Galera clusters and related technologies, and thus I hadn’t given much thought to Percona Xtradb Cluster (PXC), until Alkin approached me at FOSDEM, and proposed to extend dbdeployer features to support PXC. He mentioned that many support engineers at Percona use dbdeployer) on a daily basis and that the addition of PXC would be welcome.

I could not follow up much during the conference, but we agreed on making a proof-of-concept in an indirect way: if several nodes of PXC can run in the same host using shell scripts, dbdeployer could reproduce that behavior.

A few weeks later, when dbdeployer had already been enhanced with flavors and capabilities, I got the script that can deploy several nodes in the same host. It’s a simplification of the ones used in Percona PXC tests, which got me started.

I followed a method similar to the one I used for MySQL Group replication. The technology is similar, although the MySQL Team used a different approach for the installation. The basic principle is that the cluster needs two ports per node: in addition to the regular MySQL port, there is a communication port (SST or Snapshot State Transfer port) that is needed to exchange cluster data. Using this information, and following the sample in the script, I could produce a prototype that surprisingly worked at the first try!

The cluster did deploy, and the replication test, which comes free of charge when you implement a replication-type sandbox using standard templates, worked flawlessly.

Then I hooked the deployment method into dbdeployer concurrency engine, which is able to deploy several nodes at once. Here I hit the first problem. In PXC, the nodes are not equal at startup. The first node needs to be initialised without other nodes addresses, and it becomes the reference for other nodes to join the cluster. If I provided complete references for all nodes (as I do for MySQL Group Replication,) it didn’t work.

After some talk with Percona engineers on Slack, I figured out that the nodes can be deployed together, and the second and third node will just wait for the first one to come online and then join. That worked in principle, or when I deployed sequentially, but not when they are deployed all at once. Fortunately, dbdeployer has several ways of enabling debugging output, and after a few unsuccessful attempts I got the reason: PXC initialisation happens using rsync on port 4444. When the nodes are started sequentially, the receiving node takes control of port 4444 without conflicts, gets the job done and releases the port. When we deploy all nodes at once, there is a race for the possession of the synchronisation port, and a random node will win it, leaving the others waiting forever.

Thus, I modified the installation to allocate a different rsync port for each node, and after that the concurrent installation worked as well.

The last obstacle was the discovery that there is yet another port (IST, or Incremental State Transfer port), which is always one number bigger than the SST port. Thus, if the SST port is, say, 5555, the IST port is set to 5556. This means that, unlike other dbdeployer clusters, I can’t set port numbers incrementally, but I need to set them with an interval. I did that, and the cluster came with a default allocation of four ports per node (MySQL, rsync, SST, IST). If we also enable MySQLX, which comes includes as PXC binaries are based on MySQL 5.7, we would set 5 ports per node, and a majestic 15 ports for a three-node cluster.

Anyway, the support for Percona XtraDB Cluster is available in dbdeployer 1.21.0. Let’s see a sample session to use the new functionality.

Wednesday, March 06, 2019

After a conference, when I take stock of what I have learned, I usually realise that the best achievements are the result of interacting with other attendees during the breaks, rather than simply listening to the lectures. It might be because I follow closely the blogosphere and thus the lectures have few surprises in store for me, or perhaps because many geeks take the conference as an excuse to refresh dormant friendships, catch up with technical gossip, and ask their friends some questions that were too sensitive to be discussed over Twitter and have been waiting for a chance of an in-person meeting to see the light of the day.

I surely had some of such questions, and I took advantage of the conference to ask them. As it often happens, I got satisfactory responses, but the latest FOSDEM conference was different than usual, because I got the best experience from the questions that others did ask me.

As it turned out, others were waiting for a chance to discuss things over coffee or food, and I saw that my pet project (dbdeployer) is a lot more popular than I thought, and it is being used silently in several environments. It should not be surprising if you read several MySQL reports on bugs at bugs.mysql.com where it is common the usage of sandboxes to reproduce user issues. Anyway, I got some praise, some requests, a few ideas for improvements, advance notice of an incoming graphical interface, and a few concrete collaboration proposals.

One of such proposals came from Morgan Tocker, who suggested enhancing dbdeployer to support TiDB. At first, it seemed uninteresting, as TiDB is designed to be distributed, and installing just a component didn’t immediately look useful. However, Morgan pointed out that it could be used as a tool to test compatibility with existing applications, and as such it could gain much more value than I initially thought. We decided to try a quick hackathon to make a proof of concept.

It was a great pleasure to figure out, in just over one hour of close interaction, that dbdeployer design for flexibility was up to the task. We managed to make TiDB work with dbdeployer simply by exporting, editing, and re-loading a few templates.

The exercise showed strengths and limitations in both projects. We agreed that dbdeployer had to lose some assumptions (such as “I am working with a MySQL server”) and become able to recognise which flavor of MySQL-lookalike we are dealing with. At the same time, we noted that TiDB is not compatible when it comes to deployment and bootstrap: it is so simple and straightforward that its initialisation doesn’t fit in the complex operation that is a MySQL server warm-up.

What does transparently mean? It means that tests for TiDB deployment can run alongside tests for other MySQL servers, and the sandbox scripts (such as start, stop, use, status, and test_sb) work as expected and produce a compatible output. Thus, there is a TiDB test running together with another dozen MySQL versions.

Now, if you want, you can evaluate TiDB in your computer without installing the full stack. It won’t be as fast as the real thing: what is installed as a single node is a slower emulation of the real database, but it is enough to give you an idea of what queries you can and cannot run in TiDB, and perhaps try to see if your application could run on TiDB at all.

The collaboration with TiDB was especially useful because the changes needed to smooth the TiDB integration have made made dbdeployer better suited to add support for more not-quite-mysql servers, such as the one that we’ll see in the next post.

But before reaching that point, here’s an example of TiDB deployment on Linux:

TiDB tarballs doesn't come with a client. We need to use one from MYSQL 5.7. Rather than downloading the huge tarball from MySQL site, we can get a smaller one from a GitHub repository, using dbdeployer itself (NB: this reduced tarball is only for Linux)

Friday, April 20, 2018

When maintainng any piece of software, we usually deal with two kind of actions:

bug fixing,

new features.

bugs and features

A bug happens when there is an error in the software, which does not behave according to the documentation or the specifications. In short, it's a breech of contract between the software maintainer and the users. The promise, i.e. the software API that was published at every major version, is broken, and the software must be reconciled with the expectations and fixed, so that it behaves again as the documentation says. When we fix a bug in this way, we increment the revision number of the software version (e.g. 1.0.0 to 1.0.1. See semantic versioning).

New features, in turn, can be of two types:

backward compatible enhancements, which add value to the software without breaking the existing functionality. This is the kind of change that requires an increment of the minor indicator in the version (for example: 1.1.15 to 1.2.0.)

Incompatible changes that break the existing behavior and require users to change their workflow. This kind of change requires bumping up the major number in the version (as in 2.1.3 to 3.0.0.)

Not a bug, nor a feature, but an adjustment.

The above concepts seem simple enough: you either fix something that's broken or add new functionality.

However, when maintaining a tool that has the purpose of helping users to deal with another software (as it is the case of dbdeployer that helps users to deploy MySQL databases) there is yet another category of changes that don't fall into the standard categories: it's what happens when the software being helped (MySQL) changes its behavior, which would break the normal functioning of the helping tool, giving the maintainer a difficult choice:

shall I modify the tool's interface to adapt to the new behavior, breaking existing procedures?

or shall I adapt the tool's functioning behind the scenes to keep the interface unchanged?

My philosophy with dbdeployer (and MySQL-Sandbox before it) is to preserve the tool's interface, so that users don't have to change existing procedures. I call this kind of changes adjustments, because they are not bugs, as they are not a consequence of a coding error, and not a feature, as the intervention is not a conscious decision to add new functionality, but an emergency operation to preserve the status quo. You can think of this category as a capricious change in specifications, which so often happens to software developers, with the difference that the one changing the specs is not the user, but a third party who doesn't know, or care, about our goal of preserving the API integrity.

For example, from MySQL 8.0.3 to 8.0.4 there was a change in the default authentication plugin. Instead of mysql_native_password, MySQL 8.0.4 uses caching_sha2_password. The immediate side effect for MySQL-Sandbox and dbdeployer was that replication doesn't work out of the box. A possible solution would be to force the old authentication plugin, but this would not allow users to test the new one. Since the main reason to use a tool like dbdeployer is to experiment with new releases safely, I had to keep the default behavior. Thus, I left the default plugin in place, and changed the way the replication works. It's an ugly workaround actually, but allows users to see the new behavior without losing existing functionality.
To complete the adjustment, I added a new option --native-auth-plugin, which would deploy using the old mysql_native_password. In total, the adjustment consists of a behind-the-scenes change, almost undetectable by users, and a new option to keep using the familiar authentication if users want it.

From the point of view of semantic versioning, this kind of change is a backward-compatible modification of the API, which warrants an increase of the minor number of the version.

Another example: when MySQL went from 8.0.4 to 8.0.11, it introduced a deal breaker change: the X Plugin is now loaded by default. This is easy for users of MySQL as a document store, as they don't need to enable the plugin manually, but bad news for anyone else, as the server is opening a port and a socket that many users may not choose to open voluntarily. What's worse, when installing more sandboxes of version 8.0.11 in the same host (for example in replication), one will succeed in reserving the plugin port and socket, while the others will have the error log populated with surprising errors about a socket being already in use.

The solution is similar to the previous one. When dbdeployer detect MySQL 8.0.11 or newer, it adds options to customize the mysqlx plugin port and socket, thus allowing a frictionless deployment where the new functionality is available to the brave experimenters. At the same time, I added a new option (--disable-mysqlx) for the ones who really don't want an extra port and socket in their servers, not even for testing.

These adjustment are usually costly additions. While the added code is not that much, they require extra tests, which are often complex and require more time to write and execute them. The process to add an adjustment goes mostly like this:

I dedicate my morning walk to think about the fix. Sometimes the fix requires several walks, while I decide the less intrusive solution.

If the walk has been fruitful, writing the code requires just a few minutes. If I missed something, I iterate.

Then the more difficult part: writing meaningful tests that prove that the adjustment is correct and it doesn't introduce side effects in any MySQL version. And of course the option that reintroduces the old behavior must be tested too.

A positive side effect of this exercise is that often I realize that I was missing a test for an important behavior and then I write down that as well. The test suite included 6,000+ tests 1 month ago, and now it has almost doubled.

Tuesday, April 03, 2018

MySQL 8.0 GA is right around the corner. I don't have precise information about its release, as I don't work at Oracle. If I did, I would probably know, but I couldn't tell when the release is scheduled to appear because of company policies. I can, however, speculate and infer, based of my experience with previous releases. My personal assessment is that the release will appear before9:00am PT on April 24, 2018. The "before" can be anything from a few minutes to one week in advance.
Then, again, it may not happen at all if someone finds an atrocious bug that needs to be fixed asap.

Either way, users are keen on testing the new release in its current state of release candidate. Here I show a few methods that allow you to have a taste of the new goodies without waiting for the triumphal (keynote) announcement.

1. Docker containers

If you are a docker user, using a container to test MySQL is a no brainer. Unlike virtual machines or standalone servers, a docker container comes ready to use, with nothing to configure. All you need to do is pulling the right image. As with every docker images, you pull once and then use as many times as you need.

There are two reliable images that contain the latest MySQL. One is called mysql:8.0 and is tagged as official, which means that it is released by the Docker maintenance team. The other one, which is released by the MySQL team, is called mysql/mysql-server:8.0.

With the above commands we get two containers, one for the official image and one for the original one.
We can't use them straight away, though. We need to wait for the servers to be ready. An easy method to verify the status of the server is looking at docker logs:

Here, after about 10 seconds, both containers are ready to use. We can now access the servers. One easy method is through docker exec

$ docker exec -ti original mysql -psecret
mysql: [Warning] Using a password on the command line interface can be insecure.
Welcome to the MySQL monitor. Commands end with ; or \g.
Your MySQL connection id is 15
Server version: 8.0.4-rc-log MySQL Community Server (GPL)
Copyright (c) 2000, 2018, Oracle and/or its affiliates. All rights reserved.
Oracle is a registered trademark of Oracle Corporation and/or its
affiliates. Other names may be trademarks of their respective
owners.
Type 'help;' or '\h' for help. Type '\c' to clear the current input statement.
mysql>

A similar command would allow us to access the other container.

If you want to try replication, more work is needed. In these articles you will find more details on Docker operations, and examples of advanced deployments:

2. Sandboxes

A sandboxed database is deployed in a non-dedicated box, with its configuration altered in such a way that it will run independently from other similar deployment and even from databases running in the main space.
The granddaddy of the sandbox deployer was MySQL-Sandbox, which has recently evolved into the more powerful and easier to use dbdeployer.
You can use MySQL-Sandbox to test a MySQL 8.0 tarball on MacOS

This command unpacks the tarball into $HOME/opt/mysql and deploys the database in $HOME/sandboxes/msb_8_0_4.
Until recently, the same command would work on Linux without modifications. In MySQL 8.0.4, though, the tarball organization for Linux has changed. There are symbolic links for SSL libraries inside the ./bin directory. Those symlinks are not extracted by default, but only if you use the option --keep-directory-symlink when opening the tarball. MySQL-Sandbox doesn't do it, also because this option is not standard to every version of tar.

Thus, if you want to use the old MySQL-Sandbox, you need to run the extraction manually.

I don't recommend the above procedure, for either Linux or MacOS. The main reason, in addition to the manual operations involved, is that MySQL-Sandbox is not going to be updated for the time being. Instead, you should use dbdeployer, which has all the main features of MySQL-Sandbox and a lot of new ones. Here's the equivalent procedure:

dbdeployer uses a different method to initialize the database server, which at the same time makes the initialization more visible and avoids the problem of the phantom SSL libraries.

Note: Tarballs for recent MySQL versions are really big. MySQL 8.0.4 binaries expand to 1.9 GB. If storage is an issue, you should get the tarballs from a collection of minimised tarballs (Linux only) for most MySQL versions. For now, it's maintained by me, but I hope that the the MySQL team will release something similar.

dbdeployer creates several shortcuts for the most common commands to use the database. ./use is the most common, and provides access to the MySQL client with all the necessary options needed to use it correctly. For more information on what is available, run

$ dbdeployer usage single

This functionality would be enough to decide for a sandbox as your preferred method for testing. However, it this is only a tiny portion of what you can do with dbdeployer in your own computer. With a single command, you can test master/slave replication, multi-primary group replication, single primary group replication, fan-in, and all-masters topologies.

3. Other methods

Besides the methods that I recommend, there are others that you could use, but I won't advise about them as there are more qualified ones for that.

Standalone server. If you have the luxury of having one or more standalone servers sitting in a lab, by all means go for it. Just follow the instructions about installing MySQL on your lucky server. Be advised, though, that depending on the method you choose and the version of your operating system, you may face compatibility issues (.rpm or .deb dependencies).

Virtual machines. VMs share with standalone servers the same ease of installation (and the same dependency issues), only a bit slower. They are convenient, as you can use them to test in conditions that more closely resemble production settings, and if you use a configuration server such as Puppet or Ansible, your task of testing the new version could be greatly simplified. The instructions for the virtual machines are the same seen for standalone servers.

Monday, April 02, 2018

dbdeployer went into release candidate status a few weeks ago. Since then, I added no new features, but a lot of tests. The test suite now runs 3,000+ tests on MacOS and a bit more on Linux, for a grand total of 6,000+ tests that need to run at least twice: once with concurrency enabled and once without. I know that testing can't prove the absence of bugs, but I am satisfied with the results, since all this grinding has allowed me to find several bugs and fix them.

In this framework, I felt that dbdeployer could exit candidate status and get to version 1.0. This happened on March 26th. An immediate side effect of this change is that from this point on, dbdeployer must adhere to the semantic versioning principles:

A version number is made of Major, Minor, and Revision. When changes are applied, the following happens:

Backward-compatible new features increment the Minor number (1.0.1 to 1.1.0)

Backward incompatible changes (either features or bug fixes that break compatibility with the API) increment the Major number (1.15.9 to 2.0.0)

The starting API is defined in API-1.0.md, which was generated manually.
The file API-1.1.md contains the same API definition, but was generated automatically and can be used to better compare the initial API with further version.

So the app went from 1.0 to 1.1 in less than one week. In obedience to semantic versioning principles, if a new backward-compatible feature is added, the minor number of the version increases. What does backward-compatible mean? It means that commands, procedures, and workflows that were working with the previous version will also work with the current one. It's just that the new release will have more capabilities. In this case, the added feature is the ability of having environment variables HOME and PWD recognized and properly expanded in the configuration file. It's nothing very exciting, but changing the minor number gives the user a hint of what to expect from the new release.

Let's give a few examples:

Version goes from 1.0.0 to 1.0.1: It means that there are only bug fixes, and you should expect to use it without modifications.

Version goes from 1.0.1 to 1.1.0: You should be able to use dbdeployer just as before, but you should check the release notes to see what's new, because there are new functionalities that might be useful to you.

Version goes from 1.3.15 to 2.0.0: Danger! A major number bumped up means that something has changed in the API, which is now partially or totally incompatible with the previous release. Your workflow may break, and you must check the release notes and the documentation to learn how to use the new version.

This is different from other applications. For example, the MySQL server uses version numbers with hard to predict meaning:

MySQL 5.1, 5.5, 5.6, and 5.7 should be, in fact, major version number changes, not minor ones. Each one of them introduces incompatible changes that require careful review of the novelties.

Within the same version (such as MySQL 5.7) there are a lot of compatible and incompatible changes, although the minor number stays the same.

The plan with dbdeployer is to use the version number as a manifest, to give users an immediate feeling of what to expect. Rather than changing minor or major number only when the developers think there is some juicy new thing of which they can be proud, the version number will tell whether users should worry about compatibility or not.

In my general development plan, you are more likely to see versions like "1.25.16" than version "2.0," meaning that I will try to keep the current API valid as much as possible. A major version change will signify that a new feature could not fit in the current infrastructure and a new one would be needed.

You can draw your own conclusions here. A semantic versioning paradigm is unlikely to be adopted by most software vendors, because version numbers are often marketing gimmicks, and they can charge you more convincingly for a version 6.0 than for version 1.34.
Free software, OTOH, can do this. My goal with dbdeployer is to help the MySQL community, and I will achieve that goal more easily if my releases can be adopted without fear of incompatibility.